use "G:\My Drive\APSA_Rule_of_law\Data\Russia_analysis\stata_data\all_vars+policies_early.dta", replace
 
drop if province=="Russian Federation"
label var doc_10thou_2020 "Doctors (per 10000 people)"
label var healthypoppc "Percent healthy population"
label var pop_growth_2020 "Population growth"
label var beds_perthous_2020 "Hospital beds (per thousand people)"
label var regGDP2019rub "Regional GDP"
label var investmentsbnrub "Investment"
label var retailtradebnrub "Retail trade"
label var personnel_2016 "MVD personnel" // military/coercive capacity
gen admin_cap=fed_civil_serv_2020+local_civil_serv_2020
label var admin_cap "Federal and local civil servants" 
label var percent_internet_util "Percent of internet users"

label var cases_th_2020 "COVID cases (thousands)"
label var pol_aff_gov "United Russia leader"
gen urban_2019_new=urban_2019/10
label var urban_2019_new "Urbanization"
label var BusinessRestrictions "Business Restrictions"
label var HealthMonitoring "Health Monitoring"
label var HealthResources "Health Resources"
label var SchoolRestrictions "School Restrictions"
label var SocialDistancing "Social Distancing"

reg cases_th_2020 personnel_2016 percent_internet_util doc_10thou_2020 BusinessRestrictions HealthMonitoring HealthResources SchoolRestrictions SocialDistancing urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov
gen e = e(sample)
drop if e == 0

estpost sum cases_th_2020 personnel_2016 percent_internet_util doc_10thou_2020 beds_perthous_2020 BusinessRestrictions HealthMonitoring HealthResources SchoolRestrictions SocialDistancing urban_2019_new regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov
esttab using "G:\My Drive\APSA_Rule_of_law\Data\Russia_analysis\descriptives.rtf", label cells("mean(fmt(2)) sd(fmt(2)) min(fmt(2)) max(fmt(2))") width(1.0\hsize) nomtitle nonumber replace
*reg cases_th_2020 Capacity BusinessRestrictions HealthMonitoring HealthResources SchoolRestrictions SocialDistancing   pop_density GDPpcap FDI_pcGDP Trade_pcGDP panback polity2 female_leader 

reg cases_th_2020 personnel_2016 percent_internet_util doc_10thou_2020 BusinessRestrictions HealthMonitoring HealthResources SchoolRestrictions SocialDistancing urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov, ro  
eststo m1

reg cases_th_2020 personnel_2016 BusinessRestrictions HealthMonitoring HealthResources SchoolRestrictions SocialDistancing urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov , ro 
eststo m2

reg cases_th_2020 percent_internet_util BusinessRestrictions HealthMonitoring HealthResources SchoolRestrictions SocialDistancing urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov  , ro 
eststo m3

reg cases_th_2020 doc_10thou_2020 BusinessRestrictions HealthMonitoring HealthResources SchoolRestrictions SocialDistancing urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov , ro 
eststo m4

reg cases_th_2020 beds_perthous_2020 BusinessRestrictions HealthMonitoring HealthResources SchoolRestrictions SocialDistancing urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov , ro 
eststo m5

esttab m1 m2 m3 m4 m5 using "cases_early_Ru.tex", label se b(3) ///
eqlabels(none) nodiscrete booktabs replace  ///
order (personnel_2016 percent_internet_util doc_10thou_2020 beds_perthous_2020) ///
	mtitles("(1)" "(2)" "(3)" "(4)" "(5)" "(6)") nonumber ///
	nonotes  ///
    star(* 0.10 ** 0.05 *** .01) 

	
reg BusinessRestrictions personnel_2016 percent_internet_util doc_10thou_2020 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020 , ro 
eststo m1

reg  BusinessRestrictions personnel_2016 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020, ro 
eststo m2

reg BusinessRestrictions percent_internet_util urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020 , ro 
eststo m3

reg BusinessRestrictions doc_10thou_2020 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020 , ro 
eststo m4

reg BusinessRestrictions beds_perthous_2020 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020, ro 
eststo m5

esttab m1 m2 m3 m4 m5 using "cases_early_Ru_business.tex", label se b(3) ///
eqlabels(none) nodiscrete booktabs replace  ///
order (personnel_2016 percent_internet_util doc_10thou_2020 beds_perthous_2020) ///
	mtitles("(1)" "(2)" "(3)" "(4)" "(5)" "(6)") nonumber ///
	nonotes  ///
    star(* 0.10 ** 0.05 *** .01) 

reg HealthMonitoring personnel_2016 percent_internet_util doc_10thou_2020 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020 , ro 
eststo m1

reg  HealthMonitoring personnel_2016 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020, ro 
eststo m2

reg HealthMonitoring percent_internet_util urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020 , ro 
eststo m3

reg HealthMonitoring doc_10thou_2020 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020 , ro 
eststo m4

reg HealthMonitoring beds_perthous_2020 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020, ro 
eststo m5

esttab m1 m2 m3 m4 m5 using "cases_early_Ru_healthmon.tex", label se b(3) ///
eqlabels(none) nodiscrete booktabs replace  ///
order (personnel_2016 percent_internet_util doc_10thou_2020 beds_perthous_2020) ///
	mtitles("(1)" "(2)" "(3)" "(4)" "(5)" "(6)") nonumber ///
	nonotes  ///
    star(* 0.10 ** 0.05 *** .01) 
	
	
reg HealthResources personnel_2016 percent_internet_util doc_10thou_2020 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020 , ro 
eststo m1

reg  HealthResources personnel_2016 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020, ro 
eststo m2

reg HealthResources percent_internet_util urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020 , ro 
eststo m3

reg HealthResources doc_10thou_2020 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020 , ro 
eststo m4

reg HealthResources beds_perthous_2020 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020, ro 
eststo m5

esttab m1 m2 m3 m4 m5 using "cases_early_Ru_healthres.tex", label se b(3) ///
eqlabels(none) nodiscrete booktabs replace  ///
order (personnel_2016 percent_internet_util doc_10thou_2020 beds_perthous_2020) ///
	mtitles("(1)" "(2)" "(3)" "(4)" "(5)" "(6)") nonumber ///
	nonotes  ///
    star(* 0.10 ** 0.05 *** .01) 
	
reg SchoolRestrictions personnel_2016 percent_internet_util doc_10thou_2020 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020, ro  
eststo m1

reg SchoolRestrictions personnel_2016 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020, ro 
eststo m2

reg SchoolRestrictions percent_internet_util urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020 , ro 
eststo m3

reg SchoolRestrictions doc_10thou_2020 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020 , ro 
eststo m4

reg SchoolRestrictions beds_perthous_2020 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020, ro 
eststo m5

esttab m1 m2 m3 m4 m5 using "cases_early_Ru_school.tex", label se b(3) ///
eqlabels(none) nodiscrete booktabs replace  ///
order (personnel_2016 percent_internet_util doc_10thou_2020 beds_perthous_2020) ///
	mtitles("(1)" "(2)" "(3)" "(4)" "(5)" "(6)") nonumber ///
	nonotes  ///
    star(* 0.10 ** 0.05 *** .01) 
	
reg SocialDistancing personnel_2016 percent_internet_util doc_10thou_2020 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020 , ro 
eststo m1

reg SocialDistancing personnel_2016 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020, ro 
eststo m2

reg SocialDistancing percent_internet_util urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020, ro  
eststo m3

reg SocialDistancing doc_10thou_2020 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020 , ro 
eststo m4

reg SocialDistancing beds_perthous_2020 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020, ro 
eststo m5

esttab m1 m2 m3 m4 m5 using "cases_early_Ru_dist.tex", label se b(3) ///
eqlabels(none) nodiscrete booktabs replace  ///
order (personnel_2016 percent_internet_util doc_10thou_2020 beds_perthous_2020) ///
	mtitles("(1)" "(2)" "(3)" "(4)" "(5)" "(6)") nonumber ///
	nonotes  ///
    star(* 0.10 ** 0.05 *** .01) 		
	

use "G:\My Drive\APSA_Rule_of_law\Data\Russia_analysis\stata_data\all_vars+policies_all.dta", replace

drop if province=="Russian Federation"
label var doc_10thou_2020 "Doctors (per 10000 people)"
label var healthypoppc "Percent healthy population"
label var pop_growth_2020 "Population growth"
label var beds_perthous_2020 "Hospital beds (per thousand people)"
label var regGDP2019rub "Regional GDP"
label var investmentsbnrub "Investment"
label var retailtradebnrub "Retail trade"
label var personnel_2016 "MVD personnel" // military/coercive capacity
gen admin_cap=fed_civil_serv_2020+local_civil_serv_2020
label var admin_cap "Federal and local civil servants" 
label var percent_internet_util "Percent of internet users"

label var cases_th_2020 "COVID cases (thousands)"
label var pol_aff_gov "United Russia leader"
label var urban_2019 "Urbanization"
label var BusinessRestrictions "Business Restrictions"
label var HealthMonitoring "Health Monitoring"
label var HealthResources "Health Resources"
label var SchoolRestrictions "School Restrictions"
label var SocialDistancing "Social Distancing"


	
*reg cases_th_2020 Capacity BusinessRestrictions HealthMonitoring HealthResources SchoolRestrictions SocialDistancing   pop_density GDPpcap FDI_pcGDP Trade_pcGDP panback polity2 female_leader 

reg cases_th_2020 personnel_2016 percent_internet_util doc_10thou_2020 BusinessRestrictions HealthMonitoring HealthResources SchoolRestrictions SocialDistancing urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov , ro 
eststo m1

reg cases_th_2020 personnel_2016 BusinessRestrictions HealthMonitoring HealthResources SchoolRestrictions SocialDistancing urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov , ro 
eststo m2

reg cases_th_2020 percent_internet_util BusinessRestrictions HealthMonitoring HealthResources SchoolRestrictions SocialDistancing urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov  , ro 
eststo m3

reg cases_th_2020 doc_10thou_2020 BusinessRestrictions HealthMonitoring HealthResources SchoolRestrictions SocialDistancing urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov , ro 
eststo m4

reg cases_th_2020 beds_perthous_2020 BusinessRestrictions HealthMonitoring HealthResources SchoolRestrictions SocialDistancing urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov , ro 
eststo m5

esttab m1 m2 m3 m4 m5 using "cases_Ru.tex", label se b(3) ///
eqlabels(none) nodiscrete booktabs replace  ///
order (personnel_2016 percent_internet_util doc_10thou_2020 beds_perthous_2020) ///
	mtitles("(1)" "(2)" "(3)" "(4)" "(5)" "(6)") nonumber ///
	nonotes  ///
    star(* 0.10 ** 0.05 *** .01) 
	

reg BusinessRestrictions personnel_2016 percent_internet_util doc_10thou_2020 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020 , ro 
eststo m1

reg  BusinessRestrictions personnel_2016 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020, ro 
eststo m2

reg BusinessRestrictions percent_internet_util urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020 , ro 
eststo m3

reg BusinessRestrictions doc_10thou_2020 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020 , ro 
eststo m4

reg BusinessRestrictions beds_perthous_2020 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020, ro 
eststo m5

esttab m1 m2 m3 m4 m5 using "cases_Ru_business.tex", label se b(3) ///
eqlabels(none) nodiscrete booktabs replace  ///
order (personnel_2016 percent_internet_util doc_10thou_2020 beds_perthous_2020) ///
	mtitles("(1)" "(2)" "(3)" "(4)" "(5)" "(6)") nonumber ///
	nonotes  ///
    star(* 0.10 ** 0.05 *** .01) 

reg HealthMonitoring personnel_2016 percent_internet_util doc_10thou_2020 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020 , ro 
eststo m1

reg  HealthMonitoring personnel_2016 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020, ro 
eststo m2

reg HealthMonitoring percent_internet_util urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020 , ro 
eststo m3

reg HealthMonitoring doc_10thou_2020 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020 , ro 
eststo m4

reg HealthMonitoring beds_perthous_2020 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020, ro 
eststo m5

esttab m1 m2 m3 m4 m5 using "cases_Ru_healthmon.tex", label se b(3) ///
eqlabels(none) nodiscrete booktabs replace  ///
order (personnel_2016 percent_internet_util doc_10thou_2020 beds_perthous_2020) ///
	mtitles("(1)" "(2)" "(3)" "(4)" "(5)" "(6)") nonumber ///
	nonotes  ///
    star(* 0.10 ** 0.05 *** .01) 
	
	
reg HealthResources personnel_2016 percent_internet_util doc_10thou_2020 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020 , ro 
eststo m1

reg  HealthResources personnel_2016 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020, ro 
eststo m2

reg HealthResources percent_internet_util urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020 , ro 
eststo m3

reg HealthResources doc_10thou_2020 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020 , ro 
eststo m4

reg HealthResources beds_perthous_2020 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020, ro 
eststo m5

esttab m1 m2 m3 m4 m5 using "cases_Ru_healthres.tex", label se b(3) ///
eqlabels(none) nodiscrete booktabs replace  ///
order (personnel_2016 percent_internet_util doc_10thou_2020 beds_perthous_2020) ///
	mtitles("(1)" "(2)" "(3)" "(4)" "(5)" "(6)") nonumber ///
	nonotes  ///
    star(* 0.10 ** 0.05 *** .01) 
	
reg SchoolRestrictions personnel_2016 percent_internet_util doc_10thou_2020 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020 , ro 
eststo m1

reg SchoolRestrictions personnel_2016 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020, ro 
eststo m2

reg SchoolRestrictions percent_internet_util urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020 , ro 
eststo m3

reg SchoolRestrictions doc_10thou_2020 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020 , ro 
eststo m4

reg SchoolRestrictions beds_perthous_2020 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020, ro 
eststo m5

esttab m1 m2 m3 m4 m5 using "cases_Ru_school.tex", label se b(3) ///
eqlabels(none) nodiscrete booktabs replace  ///
order (personnel_2016 percent_internet_util doc_10thou_2020 beds_perthous_2020) ///
	mtitles("(1)" "(2)" "(3)" "(4)" "(5)" "(6)") nonumber ///
	nonotes  ///
    star(* 0.10 ** 0.05 *** .01) 
	
reg SocialDistancing personnel_2016 percent_internet_util doc_10thou_2020 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020 , ro 
eststo m1

reg SocialDistancing personnel_2016 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020, ro 
eststo m2

reg SocialDistancing percent_internet_util urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020 , ro 
eststo m3

reg SocialDistancing doc_10thou_2020 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020 , ro 
eststo m4

reg SocialDistancing beds_perthous_2020 urban_2019 regGDP2019rub investmentsbnrub retailtradebnrub pol_aff_gov cases_th_2020, ro 
eststo m5

esttab m1 m2 m3 m4 m5 using "cases_Ru_dist.tex", label se b(3) ///
eqlabels(none) nodiscrete booktabs replace  ///
order (personnel_2016 percent_internet_util doc_10thou_2020 beds_perthous_2020) ///
	mtitles("(1)" "(2)" "(3)" "(4)" "(5)" "(6)") nonumber ///
	nonotes  ///
    star(* 0.10 ** 0.05 *** .01) 		